from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 35.0 | 43.447687 |
| daal4py_KNeighborsClassifier | 0.0 | 2.0 | 51.640757 |
| KNeighborsClassifier_kd_tree | 0.0 | 2.0 | 42.632228 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 0.0 | 28.468151 |
| KMeans_tall | 0.0 | 0.0 | 24.135070 |
| daal4py_KMeans_tall | 0.0 | 0.0 | 8.792856 |
| KMeans_short | 0.0 | 0.0 | 3.218084 |
| daal4py_KMeans_short | 0.0 | 0.0 | 1.613673 |
| LogisticRegression | 0.0 | 0.0 | 21.181543 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 4.213987 |
| Ridge | 0.0 | 0.0 | 11.421237 |
| daal4py_Ridge | 0.0 | 0.0 | 2.090994 |
| HistGradientBoostingClassifier | 0.0 | 5.0 | 26.165226 |
| lightgbm | 0.0 | 5.0 | 27.185863 |
| xgboost | 0.0 | 5.0 | 21.548497 |
| total | 0.0 | 59.0 | 17.844290 |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | n_samples_train | n_samples | n_features | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 0.189 | 0.000 | 4.240 | 0.000 | 1 | 5 | NaN | NaN | 0.514 | 0.000 | 0.367 | 0.000 | See | See |
| 1 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 25.265 | 0.218 | 0.000 | 0.025 | 1 | 5 | 0.815 | 0.811 | 2.017 | 0.012 | 12.527 | 0.130 | See | See |
| 2 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 0.208 | 0.001 | 0.000 | 0.208 | 1 | 5 | 1.000 | 0.000 | 0.086 | 0.000 | 2.405 | 0.020 | See | See |
| 3 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 0.141 | 0.000 | 5.672 | 0.000 | 1 | 1 | NaN | NaN | 0.502 | 0.000 | 0.281 | 0.000 | See | See |
| 4 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 13.733 | 0.089 | 0.000 | 0.014 | 1 | 1 | 0.721 | 0.723 | 2.036 | 0.037 | 6.747 | 0.130 | See | See |
| 5 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 0.194 | 0.001 | 0.000 | 0.194 | 1 | 1 | 1.000 | 0.000 | 0.088 | 0.001 | 2.209 | 0.037 | See | See |
| 6 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 0.143 | 0.000 | 5.611 | 0.000 | -1 | 5 | NaN | NaN | 0.500 | 0.000 | 0.285 | 0.000 | See | See |
| 7 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 35.880 | 0.000 | 0.000 | 0.036 | -1 | 5 | 0.815 | 0.943 | 2.105 | 0.020 | 17.047 | 0.159 | See | See |
| 8 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 0.180 | 0.012 | 0.000 | 0.180 | -1 | 5 | 1.000 | 1.000 | 0.086 | 0.001 | 2.083 | 0.142 | See | See |
| 9 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 0.141 | 0.000 | 5.677 | 0.000 | -1 | 100 | NaN | NaN | 0.502 | 0.000 | 0.281 | 0.000 | See | See |
| 10 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 36.039 | 0.000 | 0.000 | 0.036 | -1 | 100 | 0.944 | 0.811 | 2.037 | 0.026 | 17.690 | 0.224 | See | See |
| 11 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 0.190 | 0.019 | 0.000 | 0.190 | -1 | 100 | 1.000 | 0.000 | 0.088 | 0.004 | 2.147 | 0.233 | See | See |
| 12 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 0.135 | 0.000 | 5.930 | 0.000 | -1 | 1 | NaN | NaN | 0.502 | 0.000 | 0.269 | 0.000 | See | See |
| 13 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 25.257 | 0.185 | 0.000 | 0.025 | -1 | 1 | 0.721 | 0.943 | 2.120 | 0.024 | 11.912 | 0.160 | See | See |
| 14 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 0.186 | 0.020 | 0.000 | 0.186 | -1 | 1 | 1.000 | 1.000 | 0.087 | 0.001 | 2.154 | 0.233 | See | See |
| 15 | KNeighborsClassifier | fit | 1000000 | 1000000 | 100 | 0.135 | 0.000 | 5.938 | 0.000 | 1 | 100 | NaN | NaN | 0.500 | 0.000 | 0.269 | 0.000 | See | See |
| 16 | KNeighborsClassifier | predict | 1000000 | 1000 | 100 | 24.614 | 0.162 | 0.000 | 0.025 | 1 | 100 | 0.944 | 0.723 | 2.017 | 0.015 | 12.203 | 0.123 | See | See |
| 17 | KNeighborsClassifier | predict | 1000000 | 1 | 100 | 0.202 | 0.001 | 0.000 | 0.202 | 1 | 100 | 1.000 | 0.000 | 0.088 | 0.003 | 2.300 | 0.070 | See | See |
| 18 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 0.061 | 0.000 | 0.264 | 0.000 | 1 | 5 | NaN | NaN | 0.114 | 0.000 | 0.532 | 0.000 | See | See |
| 19 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 22.151 | 0.040 | 0.000 | 0.022 | 1 | 5 | 0.989 | 0.983 | 0.318 | 0.004 | 69.713 | 0.804 | See | See |
| 20 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 0.021 | 0.000 | 0.000 | 0.021 | 1 | 5 | 1.000 | 1.000 | 0.006 | 0.001 | 3.252 | 0.524 | See | See |
| 21 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 0.061 | 0.000 | 0.262 | 0.000 | 1 | 1 | NaN | NaN | 0.113 | 0.000 | 0.540 | 0.000 | See | See |
| 22 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 10.562 | 0.024 | 0.000 | 0.011 | 1 | 1 | 0.983 | 0.973 | 0.319 | 0.004 | 33.136 | 0.431 | See | See |
| 23 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 0.015 | 0.001 | 0.000 | 0.015 | 1 | 1 | 1.000 | 1.000 | 0.006 | 0.001 | 2.434 | 0.343 | See | See |
| 24 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 0.061 | 0.000 | 0.261 | 0.000 | -1 | 5 | NaN | NaN | 0.113 | 0.000 | 0.542 | 0.000 | See | See |
| 25 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 33.254 | 0.000 | 0.000 | 0.033 | -1 | 5 | 0.989 | 0.986 | 0.371 | 0.001 | 89.541 | 0.309 | See | See |
| 26 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 0.026 | 0.001 | 0.000 | 0.026 | -1 | 5 | 1.000 | 1.000 | 0.007 | 0.001 | 3.926 | 0.491 | See | See |
| 27 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 0.061 | 0.000 | 0.263 | 0.000 | -1 | 100 | NaN | NaN | 0.113 | 0.000 | 0.537 | 0.000 | See | See |
| 28 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 33.401 | 0.000 | 0.000 | 0.033 | -1 | 100 | 0.991 | 0.983 | 0.317 | 0.002 | 105.423 | 0.736 | See | See |
| 29 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 0.026 | 0.001 | 0.000 | 0.026 | -1 | 100 | 1.000 | 1.000 | 0.007 | 0.000 | 3.874 | 0.233 | See | See |
| 30 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 0.061 | 0.000 | 0.261 | 0.000 | -1 | 1 | NaN | NaN | 0.115 | 0.000 | 0.532 | 0.000 | See | See |
| 31 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 21.879 | 0.097 | 0.000 | 0.022 | -1 | 1 | 0.983 | 0.986 | 0.372 | 0.001 | 58.826 | 0.291 | See | See |
| 32 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 0.020 | 0.001 | 0.000 | 0.020 | -1 | 1 | 1.000 | 1.000 | 0.006 | 0.001 | 3.198 | 0.426 | See | See |
| 33 | KNeighborsClassifier | fit | 1000000 | 1000000 | 2 | 0.061 | 0.000 | 0.261 | 0.000 | 1 | 100 | NaN | NaN | 0.113 | 0.000 | 0.542 | 0.000 | See | See |
| 34 | KNeighborsClassifier | predict | 1000000 | 1000 | 2 | 22.419 | 0.040 | 0.000 | 0.022 | 1 | 100 | 0.991 | 0.973 | 0.315 | 0.002 | 71.148 | 0.576 | See | See |
| 35 | KNeighborsClassifier | predict | 1000000 | 1 | 2 | 0.021 | 0.001 | 0.000 | 0.021 | 1 | 100 | 1.000 | 1.000 | 0.006 | 0.001 | 3.300 | 0.558 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | n_samples_train | n_samples | n_features | mean_sklearn | stdev_sklearn | throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.234 | 0.000 | 0.025 | 0.000 | 1 | 100 | NaN | NaN | 0.743 | 0.000 | 4.353 | 0.000 | See | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 4.827 | 0.023 | 0.000 | 0.005 | 1 | 100 | 0.973 | 0.978 | 0.187 | 0.003 | 25.862 | 0.394 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.013 | 0.001 | 0.000 | 0.013 | 1 | 100 | 1.000 | 1.000 | 0.001 | 0.000 | 24.869 | 8.930 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.227 | 0.000 | 0.025 | 0.000 | 1 | 1 | NaN | NaN | 0.729 | 0.000 | 4.426 | 0.000 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.762 | 0.008 | 0.000 | 0.001 | 1 | 1 | 0.965 | 0.975 | 0.553 | 0.007 | 1.378 | 0.022 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 1.000 | 1.000 | 0.001 | 0.000 | 2.117 | 0.785 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.286 | 0.000 | 0.024 | 0.000 | 1 | 5 | NaN | NaN | 0.719 | 0.000 | 4.567 | 0.000 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.469 | 0.011 | 0.000 | 0.001 | 1 | 5 | 0.971 | 0.975 | 0.548 | 0.006 | 2.681 | 0.034 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 5 | 1.000 | 1.000 | 0.001 | 0.000 | 4.096 | 1.598 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.236 | 0.000 | 0.025 | 0.000 | -1 | 100 | NaN | NaN | 0.759 | 0.000 | 4.263 | 0.000 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2.644 | 0.026 | 0.000 | 0.003 | -1 | 100 | 0.973 | 0.978 | 0.183 | 0.003 | 14.415 | 0.282 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.016 | 0.001 | 0.000 | 0.016 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 32.276 | 12.748 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.288 | 0.000 | 0.024 | 0.000 | -1 | 1 | NaN | NaN | 0.713 | 0.000 | 4.612 | 0.000 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.428 | 0.003 | 0.000 | 0.000 | -1 | 1 | 0.965 | 0.954 | 0.100 | 0.001 | 4.295 | 0.039 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 12.541 | 5.624 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.251 | 0.000 | 0.025 | 0.000 | -1 | 5 | NaN | NaN | 0.736 | 0.000 | 4.415 | 0.000 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.808 | 0.009 | 0.000 | 0.001 | -1 | 5 | 0.971 | 0.954 | 0.102 | 0.002 | 7.919 | 0.150 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | 0.000 | 0.006 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 17.122 | 5.982 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 0.857 | 0.000 | 0.019 | 0.000 | 1 | 100 | NaN | NaN | 0.500 | 0.000 | 1.714 | 0.000 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 0.056 | 0.001 | 0.000 | 0.000 | 1 | 100 | 0.990 | 0.981 | 0.001 | 0.001 | 42.875 | 17.952 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 5.704 | 3.955 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 0.840 | 0.000 | 0.019 | 0.000 | 1 | 1 | NaN | NaN | 0.497 | 0.000 | 1.690 | 0.000 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 0.025 | 0.001 | 0.001 | 0.000 | 1 | 1 | 0.981 | 0.983 | 0.007 | 0.001 | 3.481 | 0.412 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 5.292 | 3.533 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 0.852 | 0.000 | 0.019 | 0.000 | 1 | 5 | NaN | NaN | 0.487 | 0.000 | 1.749 | 0.000 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 0.028 | 0.001 | 0.001 | 0.000 | 1 | 5 | 0.991 | 0.983 | 0.007 | 0.001 | 3.711 | 0.589 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 5.307 | 3.541 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 0.859 | 0.000 | 0.019 | 0.000 | -1 | 100 | NaN | NaN | 0.529 | 0.000 | 1.623 | 0.000 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 0.049 | 0.001 | 0.000 | 0.000 | -1 | 100 | 0.990 | 0.981 | 0.001 | 0.000 | 39.117 | 14.524 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 100 | 1.000 | 1.000 | 0.000 | 0.000 | 20.413 | 14.102 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 0.857 | 0.000 | 0.019 | 0.000 | -1 | 1 | NaN | NaN | 0.506 | 0.000 | 1.695 | 0.000 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 0.029 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.981 | 0.972 | 0.001 | 0.000 | 27.264 | 7.324 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 1.000 | 1.000 | 0.000 | 0.000 | 21.759 | 15.193 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 2 | 0.836 | 0.000 | 0.019 | 0.000 | -1 | 5 | NaN | NaN | 0.497 | 0.000 | 1.682 | 0.000 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 2 | 0.030 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.991 | 0.972 | 0.001 | 0.000 | 38.087 | 10.719 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 1.000 | 1.000 | 0.000 | 0.000 | 21.173 | 14.721 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.668 | 0.0 | 0.719 | 0.000 | random | NaN | 30 | NaN | 0.492 | 0.0 | 1.356 | 0.000 | See | See |
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.001 | 0.0 | 0.320 | 0.000 | random | 0.001 | 30 | 0.001 | 0.000 | 0.0 | 9.735 | 5.627 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.001 | 0.0 | 0.000 | 0.001 | random | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 10.552 | 6.480 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 30 | 0.643 | 0.0 | 0.746 | 0.000 | k-means++ | NaN | 30 | NaN | 0.460 | 0.0 | 1.398 | 0.000 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 30 | 0.001 | 0.0 | 0.330 | 0.000 | k-means++ | 0.001 | 30 | 0.001 | 0.000 | 0.0 | 7.688 | 3.712 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 30 | 0.001 | 0.0 | 0.000 | 0.001 | k-means++ | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 9.752 | 5.781 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 6.464 | 0.0 | 3.713 | 0.000 | random | NaN | 30 | NaN | 3.080 | 0.0 | 2.099 | 0.000 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.0 | 13.081 | 0.000 | random | 0.002 | 30 | 0.002 | 0.000 | 0.0 | 6.235 | 2.958 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.001 | 0.0 | 0.017 | 0.001 | random | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 9.640 | 5.355 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 30 | 6.474 | 0.0 | 3.707 | 0.000 | k-means++ | NaN | 30 | NaN | 2.933 | 0.0 | 2.207 | 0.000 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 30 | 0.002 | 0.0 | 13.075 | 0.000 | k-means++ | 0.002 | 30 | 0.002 | 0.000 | 0.0 | 5.948 | 2.513 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 30 | 0.001 | 0.0 | 0.017 | 0.001 | k-means++ | 1.000 | 30 | 1.000 | 0.000 | 0.0 | 10.551 | 6.446 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 20 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | n_samples_train | n_samples | n_features | n_iter_sklearn | mean_sklearn | stdev_sklearn | throughput | latency | init | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.096 | 0.0 | 0.033 | 0.000 | random | NaN | 20 | NaN | 0.102 | 0.0 | 0.942 | 0.000 | See | See |
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.161 | 0.000 | random | -0.000 | 20 | 0.001 | 0.001 | 0.0 | 2.820 | 0.523 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.001 | 0.0 | 0.000 | 0.001 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.194 | 5.932 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 20 | 0.274 | 0.0 | 0.012 | 0.000 | k-means++ | NaN | 20 | NaN | 0.035 | 0.0 | 7.903 | 0.000 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 20 | 0.002 | 0.0 | 0.151 | 0.000 | k-means++ | 0.001 | 20 | 0.000 | 0.001 | 0.0 | 2.703 | 0.527 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 20 | 0.001 | 0.0 | 0.000 | 0.001 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 10.156 | 5.844 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 0.229 | 0.0 | 0.700 | 0.000 | random | NaN | 20 | NaN | 0.393 | 0.0 | 0.582 | 0.000 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.003 | 0.0 | 5.619 | 0.000 | random | 0.316 | 20 | 0.326 | 0.001 | 0.0 | 2.073 | 0.410 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.002 | 0.0 | 0.010 | 0.002 | random | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 8.606 | 4.678 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 20 | 0.677 | 0.0 | 0.236 | 0.000 | k-means++ | NaN | 20 | NaN | 0.150 | 0.0 | 4.508 | 0.000 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 20 | 0.003 | 0.0 | 5.361 | 0.000 | k-means++ | 0.308 | 20 | 0.326 | 0.001 | 0.0 | 2.172 | 0.472 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 20 | 0.002 | 0.0 | 0.010 | 0.002 | k-means++ | 1.000 | 20 | 1.000 | 0.000 | 0.0 | 7.986 | 3.806 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | class_weight | l1_ratio | n_jobs | random_state | accuracy_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | [20] | 11.829 | 0.0 | [-0.09974773] | 0.000 | NaN | NaN | NaN | NaN | NaN | 1.975 | 0.0 | 5.990 | 0.000 | See | See |
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | [20] | 0.000 | 0.0 | [45.56666275] | 0.000 | NaN | NaN | NaN | NaN | 0.534 | 0.000 | 0.0 | 0.905 | 0.391 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | [20] | 0.000 | 0.0 | [0.18062564] | 0.000 | NaN | NaN | NaN | NaN | 0.000 | 0.000 | 0.0 | 0.447 | 0.347 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | [26] | 0.831 | 0.0 | [2.50173673] | 0.001 | NaN | NaN | NaN | NaN | NaN | 0.723 | 0.0 | 1.150 | 0.000 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | [26] | 0.002 | 0.0 | [115.37611365] | 0.000 | NaN | NaN | NaN | NaN | 0.350 | 0.003 | 0.0 | 0.559 | 0.097 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | [26] | 0.000 | 0.0 | [19.66137071] | 0.000 | NaN | NaN | NaN | NaN | 0.000 | 0.001 | 0.0 | 0.138 | 0.089 | See | See |
All estimators share the following hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | deprecated |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
| estimator | function | n_samples_train | n_samples | n_features | n_iter | mean_sklearn | stdev_sklearn | throughput | latency | max_iter | random_state | r2_score | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | sklearn_profiling | daal4py_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | NaN | 0.195 | 0.0 | 0.411 | 0.0 | NaN | NaN | NaN | 0.195 | 0.000 | 0.996 | 0.000 | See | See |
| 1 | Ridge | predict | 1000 | 1000 | 10000 | NaN | 0.011 | 0.0 | 7.575 | 0.0 | NaN | NaN | 0.114 | 0.017 | 0.001 | 0.613 | 0.031 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | NaN | 0.000 | 0.0 | 1.069 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.568 | 0.487 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | NaN | 1.459 | 0.0 | 0.548 | 0.0 | NaN | NaN | NaN | 0.261 | 0.000 | 5.581 | 0.000 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | NaN | 0.000 | 0.0 | 2.610 | 0.0 | NaN | NaN | 1.000 | 0.000 | 0.000 | 1.202 | 0.685 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | NaN | 0.000 | 0.0 | 0.012 | 0.0 | NaN | NaN | NaN | 0.000 | 0.000 | 0.637 | 0.611 | See | See |
{
"system_info": {
"python": "3.8.10 | packaged by conda-forge | (default, May 11 2021, 07:01:05) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1047-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1.2",
"setuptools": "49.6.0.post20210108",
"sklearn": "1.0.dev0",
"numpy": "1.20.3",
"scipy": "1.6.3",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": "3.4.2",
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.15.so",
"prefix": "libopenblas",
"user_api": "blas",
"internal_api": "openblas",
"version": "0.3.15",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/python3.8/site-packages/scikit_learn.libs/libgomp-f7e03b3e.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}